This relates generally to imaging devices, and more particularly, to imaging devices with clear image pixels.
Image sensors are commonly used in electronic devices such as cellular telephones, cameras, and computers to capture images. In a typical arrangement, an electronic device is provided with an array of image pixels arranged in pixel rows and pixel columns. Circuitry is commonly coupled to each pixel column for reading out image signals from the image pixels.
Conventional imaging systems employ a single image sensor in which the visible light spectrum is sampled by red, green, and blue (RGB) image pixels arranged in a Bayer mosaic pattern. The Bayer Mosaic pattern consists of a repeating cell of two-by-two image pixels, with two green pixels diagonally opposite one another, and the other corners being red and blue. However, the Bayer pattern does not readily enable further miniaturization of image sensors via smaller image pixel sizes because of limitations of signal to noise ratio (SNR) in the image signals captured from the image pixels.
One means of improving SNR is to increase the available image signal by increasing light exposure at low light levels, where SNR limits the image quality. One conventional method is the use of subtractive filters, in which, for example, red, green, and blue image pixels are replaced by cyan, magenta, and yellow image pixels. However, these signals must generally be converted to RGB or some equivalent output image signal colors to be able to drive most conventional image displays. This transformation generally involves the modification of captured image signals using a color correction matrix (CCM), which can amplify noise, so that the effect of the exposure increase is compromised.
It would therefore be desirable to be able to provide imaging devices with improved means of capturing and processing image signals.